Factors influencing injury severity in three-wheeled motorized rickshaw and motorcycle collisions

Crashes involving three-wheeler motorized rickshaws (3-WMR) and motorcycles are becoming a rising public health and socioeconomic problem in developing countries. While earlier studies have investigated safety-related issues for two, and four-wheelers, there exists a notable research gap to understanding the factors that contribute to the severity of injuries in involving 3-WMR collisions with motorcyclists. The current study aims to fill this gap by investigating the risk factors contributing to injury severity in such crashes, employing a random parameters multinomial logit model with heterogeneity in means and variance. The study conducted an empirical analysis using traffic crash data spanning three years (2019-2021) from RESCUE 1122 in Rawalpindi, Pakistan. The model outcomes demonstrate that major injuries (severe and fatal) in 3-WMR and motorcycle collisions are affected by numerous factors, including road features, driver characteristics, temporal factors and environmental factors. The study provides beneficial findings, emphasizing the significance of accounting for unobserved heterogeneity in the variables contributing to injury severity in 3-WMR and motorcycle collisions. Based on the findings of the study, policy recommendations are provided to help safety practitioners build more effective strategies to address the safety concerns regarding 3-WMR crashes with motorcycles in Pakistan and other regions with similar safety issues.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-05-26
DOI
https://doi.org/10.1038/s41598-025-00145-9
Citations
2
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
2.61

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Factors influencing injury severity in three-wheeled motorized rickshaw and motorcycle collisions

Emmanuel Kofi Adanu, Arshad Jamal, Yahya Almarhabi, Zia ur Rehman et al.
2 citations
Scientific Reports
Traffic and Road Safety
2.61
article

Factors influencing injury severity in three-wheeled motorized rickshaw and motorcycle collisions

Emmanuel Kofi Adanu, Arshad Jamal, Yahya Almarhabi, Zia ur Rehman, Chaozhe Jiang
article en
2 citations

Abstract

Crashes involving three-wheeler motorized rickshaws (3-WMR) and motorcycles are becoming a rising public health and socioeconomic problem in developing countries. While earlier studies have investigated safety-related issues for two, and four-wheelers, there exists a notable research gap to understanding the factors that contribute to the severity of injuries in involving 3-WMR collisions with motorcyclists. The current study aims to fill this gap by investigating the risk factors contributing to injury severity in such crashes, employing a random parameters multinomial logit model with heterogeneity in means and variance. The study conducted an empirical analysis using traffic crash data spanning three years (2019-2021) from RESCUE 1122 in Rawalpindi, Pakistan. The model outcomes demonstrate that major injuries (severe and fatal) in 3-WMR and motorcycle collisions are affected by numerous factors, including road features, driver characteristics, temporal factors and environmental factors. The study provides beneficial findings, emphasizing the significance of accounting for unobserved heterogeneity in the variables contributing to injury severity in 3-WMR and motorcycle collisions. Based on the findings of the study, policy recommendations are provided to help safety practitioners build more effective strategies to address the safety concerns regarding 3-WMR crashes with motorcycles in Pakistan and other regions with similar safety issues.

Scientific ReportsVol. 15(1)
University of Alabama (US), Southwest Jiaotong University (CN)
King Abdulaziz University
Openalex Percentile: Top 12%
Traffic and Road Safety
2.61
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.